Journal of Artificial Intelligence and Data Mining (Jul 2022)
Energy-Efficient Timing Assignment of Tasks to Actors in WSANs
Abstract
Minimizing make-span and maximizing remaining energy are usually of chief importance in the applications of wireless sensor actor networks (WSANs). Current task assignment approaches are typically concerned with one of the timing or energy constraints. These approaches do not consider the types and various features of tasks WSANs may need to perform and thus may not be applicable to some types of real applications such as search and rescue missions. To this end, an optimized and type aware task assignment approach called TATA is proposed that considers the energy consumption as well as the make-span. TATA is an optimized task assignment approach and aware of the distribution necessities of WSANs with hybrid architecture. TATA comprises of two protocols, namely a Make-span Calculation Protocol (MaSC) and an Energy Consumption Calculation Protocol (ECal). Through considering both time and energy, TATA makes a tradeoff between minimizing make-span and maximizing the residual energies of actors. A series of extensive simulation results on typical scenarios show shorter make-span and larger remaining energy in comparison to when stochastic task assignment (STA), opportunistic load balancing (OLB), and task assignment algorithm based on quasi-Newton interior point (TA-QNIP) approaches is applied.
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